Discover AI Agent Skills

Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral strategies. Use when user requests pair trading opportunities, statistical arbitrage screening, mean-reversion strategies, or market-neutral portfolio construction. Supports correlation analysis, cointegration testing, and spread backtesting.

Zbrain integration. Manage data, records, and automate workflows. Use when the user wants to interact with Zbrain data.

Use when building, modifying, or debugging NetSuite UIF SPA components. Provides API/type lookup for `@uif-js/core` and `@uif-js/component` (constructors, methods, props, enums, hooks, and component options).

Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.

Ultimate stealth browser automation with anti-detection, Cloudflare bypass, CAPTCHA solving, persistent sessions, and silent operation. Use for any web automation requiring bot detection evasion, login persistence, headless browsing, or bypassing security measures. Triggers on "bypass cloudflare", "solve captcha", "stealth browse", "silent automation", "persistent login", "anti-detection", or any task needing undetectable browser automation. When user asks to "login to X website", automatically use headed mode for login, then save session for future headless reuse.

Test-driven development via red-green-refactor with an auditable commit protocol. Use when implementing any feature, bugfix, refactor, or behavior change before writing implementation code, or when the user mentions TDD, red-green-refactor, or test-first development.

Expertise in using open-multi-agent, a TypeScript framework for building production-grade multi-agent AI teams with task scheduling, dependency graphs, and inter-agent communication.

Convert local Markdown files to Feishu (Lark) documents with automatic image uploading. Uses the feishu-docx CLI tool.

Audit web pages for performance optimization following PageSpeed Insights guidelines. Use when analyzing page performance, optimizing web applications, reviewing performance metrics, implementing Core Web Vitals improvements, or when the user mentions page speed, performance optimization, Lighthouse scores, or Core Web Vitals.

Download bounded public attachment files for exact Regulations.gov comment IDs through the Tiangong CLI. Use when selected regulatory comments have supporting files that must be acquired locally with source lineage, SHA-256 hashes, byte counts, and a manifest; do not use for comment search, arbitrary URL download, file safety certification, text extraction, stance analysis, legal interpretation, or evidence synthesis.

Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration

微信公众号文章排版引擎，将 Markdown 转换为可直接粘贴到公众号编辑器的 HTML。主题风格从 references/theme-index.md 注册的自定义主题库中选取，自动章节编号、关键词下划线标记、引言卡片、目录导航、代码块、图片/GIF、作者签名。支持 Markdown / Word(.docx) / PDF / 纯文本输入（非 Markdown 先自动归一化），也支持"一键自动排版"（自动推断结构+选主题），还支持根据用户描述/参考图生成自定义主题组件库并保存本地复用。触发场景：(1) 用户提到"公众号排版""公众号文章""微信排版""gzh"，(2) 用户想把文章（md/docx/pdf/纯文本）转成公众号 HTML，(3) 用户说"自动排版""一键排版"公众号内容，(4) 用户想为公众号排版"生成新主题/自定义风格/按这张图做一套组件库"。不用于生成普通网页/落地页/PPT（用前端或 PPT 类 skill）。

Pure-Python legacy Word (.doc) → .docx converter. Parses the Word 97/2000/2002/2003 binary format (and the Word-97-compatible output written by WPS Office) directly — no LibreOffice, no Microsoft Word, no textutil, no antiword/catdoc, no external binaries of any kind. Only olefile + python-docx + lxml. Triggers when: Converting a .doc file to .docx while preserving text, fonts (incl. 宋体/黑体/仿宋 Chinese fonts), sizes, bold/italic/underline, colours, paragraph alignment/indentation/spacing/line-spacing, page setup (A4, margins, orientation), the Normal/Heading style defaults and tables — "把 doc 原样转成 docx，但不装 Word、不用 LibreOffice". Commands: - /doc2docx <文件.doc> [-o 输出.docx] - Convert one .doc to .docx - /doc2docx batch <目录> [-o 输出目录] - Batch-convert every .doc in a directory - /doc2docx inspect <文件.doc> - Print structure: FIB, fonts, paragraphs, text preview - /doc2docx check <输出.docx> [--against 原.doc] - Verify the produced .docx and diff text against the original - /转docx <文件> - 中文命令别名（单文件转换） Capabilities: OLE2/CFB parsing (olefile), FIB + CLX piece-table text extraction (UTF-16LE / cp1252), CHPX/PAPX FKP-page decoding into character & paragraph formatting, STSH style-chain resolution, STTBF ffn font-name table (with WPS UTF-16 auto-detection), PlcfSed/SEPX page setup, table reconstruction from fInTable/fTtp marks + TDefTable column widths + TTableBorders, PAGE/NUMPAGES field-code preservation, python-docx + lxml OOXML output with per-run rPr / per-paragraph pPr / per-section sectPr, batch CLI, structural inspect, fidelity check, 23-check self-test with an in-memory synthetic .doc

Emit and query Vercel Custom Metrics. Use when instrumenting application or business measurements in Vercel Functions, using metric() from @vercel/functions, choosing metric names and attributes, or querying emitted values with vc metrics.

Swap faces between images using EachLabs AI. Use when the user wants to replace or swap faces in photos.

LastPass Enterprise API integration. Manage data, records, and automate workflows. Use when the user wants to interact with LastPass Enterprise API data.

Cluster keywords by SERP overlap and design hub-and-spoke content architecture with internal links. Use for planning only; use the blog-cluster command to execute article production.

Designs album concepts, tracklist architecture, and thematic planning through 7 structured phases. Use when planning a new album or reworking an existing album concept.